Li Ruidan, Cheng Ke, Wei Zhigong, Liu Zheran, Peng Xingchen
Department of Biotherapy, Cancer Center, the State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, China.
Department of Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Front Oncol. 2022 Apr 5;12:840367. doi: 10.3389/fonc.2022.840367. eCollection 2022.
This study aimed to investigate the prognostic factors of penile cancer and establish a comprehensive predictive model for clinical application.
A total of 581 patients from the Surveillance, Epidemiology, and End Results (SEER) program (2000-2018) were used to develop the prognostic model. The multivariate Cox proportional hazards regression was performed to identify independent prognostic factors to develop the nomogram. The performance of this model was validated internally by a cohort with 143 patients from the SEER database and validated externally by a cohort with 70 patients from the West China Hospital, Sichuan University (2010-2020).
Age, marital status, size of the primary lesion, primary tumor (T), regional lymph nodes status, distant metastasis (M), and the surgery of regional lymph node (LND) were the independent prognostic factors for overall survival (OS) and were incorporated in the prognostic model. The prognostic nomogram showed a good risk stratification ability for OS in the development cohort, internal validation cohort, and external validation cohort.
This study incorporates the clinical, pathological, and therapeutic features comprehensively to develop a novel and clinically effective prognostic model for patients with penile cancer.
本研究旨在探讨阴茎癌的预后因素,并建立一个可供临床应用的综合预测模型。
利用监测、流行病学和最终结果(SEER)计划(2000 - 2018年)中的581例患者来建立预后模型。进行多变量Cox比例风险回归分析以确定独立的预后因素,从而构建列线图。该模型的性能在内部通过来自SEER数据库的143例患者队列进行验证,在外部通过四川大学华西医院的70例患者队列(2010 - 2020年)进行验证。
年龄、婚姻状况、原发灶大小、原发肿瘤(T)、区域淋巴结状态、远处转移(M)以及区域淋巴结清扫术(LND)是总生存期(OS)的独立预后因素,并被纳入预后模型。预后列线图在开发队列、内部验证队列和外部验证队列中对OS均显示出良好的风险分层能力。
本研究综合纳入临床、病理和治疗特征,为阴茎癌患者开发了一种新型且临床有效的预后模型。